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Abstract

Until recently, whole-proteome microarrays for comprehensive studies of protein interactions were mostly produced by individual cloning and cellular expression of very many open reading frames, followed by protein isolation and purification as well as array production. To overcome this cumbersome process, we have developed a method to generate microarrays representing entire proteomes by a combination of multiple spotting and on-chip, cell-free protein expression. Here, we describe the protocol for the production of bacterial protein microarrays. With slight adaptations, however, the procedure can be applied to the proteome of any organism. Expression constructs of each gene are generated by PCR on bacterial genomic DNA followed by a common secondary amplification that is adding relevant regulative elements to either end of the constructs. The unpurified PCR-products are spotted onto the microarray surface. Full-length proteins are directly expressed in situ in a cell-free manner and stay attached to the surface without further action. As an example of a typical application, we describe here the proteome-wide analysis of the immune response to a bacterial infectious agent by characterizing the binding profiles of the antibodies in patient sera.

Protein microarrays are an excellent tool for identifying disease-associated antibody reactivity patterns since they allow the simultaneous detection of antibody binding to a large number of antigens, up to entire bacterial proteomes (Hufnagel et al., 2018) and beyond (Syafrizayanti et al., 2017). Protein microarrays used to be generated with proteins that were isolated from recombinant cellular libraries. This approach is work-intensive, time-consuming and costly, however, since it requires the individual handling of very many cells. Each gene of interest is amplified by a polymerase chain reaction (PCR), followed by cloning into an expression vector. After transformation into a cellular system–frequently Escherichia coli (E. coli)–the cell clones are grown separately from others and characterized. Subsequently, the respective overexpressed protein is isolated and purified, followed by immobilization on the microarray. Our largest array of a non-mammalian gene set consisted of 14,000 proteins (Syafrizayanti et al., 2017), for example. Therefore, producing this array would have required going through the above process 14,000 times.

In order to overcome the complex procedure, means have been developed for the production of protein microarrays by cell-free protein expression directly on the microarray surface. After the initial publication of the method (Protein in situ Arrays, PISA) (He and Taussig, 2001), several adaptations have been reported (Ramachandran et al., 2004; Angenendt et al., 2006; He et al., 2008). All have in common that genes are copied into DNA expression constructs by PCR, which are directly placed onto the microarray surface. Proteins are then synthesized in situ using cell lysates containing all elements and ingredients required for transcription and translation. All steps are done in parallel and in a largely automated manner. No cells are involved throughout. In addition, the approach eliminates the need for protein purification.

Besides many minor variations, our protocol differs from the others mainly by the fact that multiple spotting is applied to produce protein microarrays (Angenendt et al., 2006; Syafrizayanti et al., 2017). First, the DNA expression constructs are placed on planar glass slides. In a second step, each position is revisited to deposit in a second spotting event a cell-free transcription and translation mixture on top of the DNA spots. Proteins are expressed directly on the microarray slide and bind immediately. The double-spotting protocol decreases substantially the volume of cell lysate needed for protein expression since the empty surface in between spots is not covered. Concomitantly, there is less background signal in between the spots eventually. More importantly, however, the reaction space is restricted to the locations of the DNA expression constructs. In consequence, expressed protein cannot float away but binds in situ only. No additional means, such as antibodies, are required to keep the proteins attached to their exact positions. Nevertheless, even extensive washing will not remove them. Previous studies have shown that most proteins are expressed in full-length, and very many fold into a functionally active conformation. Also, the process is versatile and can be adapted to fit to a variety of applications (Syafrizayanti et al., 2017).

Besides studies on microarrays with human or parasite proteins, we have used arrays that represent entire bacterial proteomes to screen clinically characterized patient (and control) sera in order to identify antibody binding patterns that are disease-specific. New marker molecules for disease diagnosis and prognosis were discovered in this way, including markers for cancer entities that are associated with bacterial infections. In a recent study, microarrays were produced that present all proteins of Chlamydia trachomatis (Ct), for example (Hufnagel et al., 2018). Through comparison of the antibody binding patterns on the microarrays, we identified antigens that are reproducibly recognized by the antibodies in Ct-seropositive samples, in addition to molecules that were patient-specific. With samples from cervical cancer patients, we found the common Ct-specific markers and additional antigens, which were shared between the cancer patients only. Large-scale validation experiments using high-throughput suspension bead array serology on hundreds of samples confirmed the significance and relevance of the newly identified markers for both general Ct infection and related cervical cancer. Next to providing meaningful marker molecules, the results strongly support the hypothesis that there is an association of Ct infection with cervical cancer.

The quick and efficient proteome-wide immunoassay can easily be adapted to other microorganisms in all areas of infection research. By reverse transcribing RNA to DNA-templates, the protocol is applicable to any transcript isolate. We also have utilized established ORF libraries, such as the Human ORFeome library (The ORFeome Collaboration, 2016), by which the process of microarray production is simplified further since only one vector-specific primer pair is required for the initial PCR. Here, we provide a detailed protocol for the production of whole-proteome bacterial microarrays and their application to screening patient sera for the immune response in infected people.

Figure 1. Images of protein microarrays made from bacterial genes. About 1,500 proteins were produced on each array. Blue boxes indicate controls. A-B. Two examples of analyses are presented that were performed using the protocol described below. Signals that were common to a group of patients are labeled by green boxes. C-E. Few examples of technical problems are presented. C. An artifact is shown, which was due to a technical fault of the spotting device, resulting in a signal gradient across the microarray. D. In a close-up, background signals on 40 microarray positions are shown. The only difference between the top and bottom half was the quality of the DNA-polymerase used for PCR. After spotting unpurified PCR-products, incubation with patient serum and subsequent labeling produced significant differences in background signal. E. A complete protein microarray is shown after incubation with patient serum and detection of antibody binding. Because of inadequate blocking, a relatively high level of background signal was produced.

For the initial PCR, design gene-specific primers in a way that each primer pair is binding at the beginning and end of each ORF and is yielding an in-frame PCR-product. Primer length should be between 16 and 24 nucleotides (nt).Note: For primer design, a Perl script can be generated to design primers using the ORF table information text file and fasta sequence(s) of the reference genome.

Calculate the melting temperature of possible primers of different length with MELTTEMP (http://www.biology.wustl.edu/gcg/melttemp.html).Note: Other software packages or websites could be used instead. However, this software was found to be useful for calculating melting temperatures of many primers required for whole-proteome projects.

Choose the best fitting primers within a range of the melting temperatures of either 45 °C-55 °C or 55 °C-65 °C.Note: Primers used in a single microtiter plate should have a similar melting temperature. If no suitable primers are found that represent the very end of an ORF, consider primer sequences that start one or two triplets downstream of the ATG start codon of the gene of interest.

Polymerase chain reaction
Perform two successive PCRs for each gene. The first PCR amplifies the gene of interest; the second PCR adds the elements needed for generating expression constructs. For the measurement of DNA concentrations, we use the NanoDrop spectrophotometer, since only small volumes are required. However, any other spectrophotometer could be used instead.Note: Concerning the overall reaction, basically all PCR amplifications were successful up to a size of some 3 kb. For larger molecules, the yield varied although the polymerase used was suitable for synthesizing long fragments.

The first PCR is performed using genomic bacterial DNA as template.Note: Genomic DNA can be obtained from the German Collection of Microorganisms and Cell Cultures (DSMZ), for example. As already mentioned in the background section above, also cDNA made from RNA preparations, existing ORF-libraries or any other molecule type that can be PCR-amplified could be used as templates.

Perform all PCR in 96-well PCR-plates–one well per gene–and group the genes based on the gene length and the melting temperatures of the respective primer pair.

Use an annealing temperature (TA) that is 2 °C below the average melting temperature of all primers within each 96-well plate.

Calculate the elongation time (timeE) as listed in the following table:

Rinse slides four times in sterile-filtered water and dry them with compressed air.

Store slides in manufacturer’s storage boxes at 4 °C for a maximum of 3 months.

Spotting of protein microarrays
Before each spotting procedure, the Nanoplotter 2.0 has to be washed twice with ddH2O for at least 20 min.

Transfer 45 µl each of all final PCR-products into 384-well plates.

Add 5 µl 5 M betaine to each well and mix plates using a microplate mixer; centrifuge all plates at about 400 x g for 1 min to collect the entire volume at the bottom.

Place up to 33 Ni-NTA-coated slides onto the slide tablet of the Nanoplotter.

Design a work plate within the Nanoplotter software, containing information about the microarray pattern: number of rows and columns, distance between spots, spot distance to edges of the slide, number and distance of blocks as well as information about the type of the 384-well plate.

Transfer the 50 µl expression mixture to a new well of a 384-well microplate.Note: Avoid air bubbles while handling the expression mixture.

Dispense with the Nanoplotter 2.4 nl expression mixture directly on top of each spot of a expression construct.Note: Transfer the expression mixture slide by slide. One piezo element of the spotter can produce a maximum of 800 spots using one sample uptake. If necessary, use multiple piezo elements for spotting the expression mixture or multiple sample uptakes per slide.

Place the slide immediately into a microarray hybridization cassette containing 30 µl of nuclease-free water in each reservoir.

Transfer the cassettes into a ventilated oven and incubate at 30 °C overnight.

Store slides without loss of reactivity at -20 °C for a maximum of 3 months.

Determination of on-chip protein expression by antibody stainingNote: To avoid drying, perform all subsequent steps immediately after one another. All washing and incubation steps are performed at room temperature unless stated otherwise on an orbital shaker set to 50 rpm.

Take slides from the freezer and place them into ProPlate Slide Modules.

Remove slides from the ProPlate Slide Modules, place them into quadriPerm chambers and wash three times with 5 ml PBST each for 10 min.

Rinse slides in sterile-filtered water and air-dry them in a ventilated oven at 30 °C by using slide staining and storage systems.

Scan slides in a Power Scanner at excitation wavelengths of 532 nm and 635 nm.

Proteome immunoassayNote: To avoid drying, perform all subsequent steps immediately after one another. All washing and incubation steps are performed at room temperature unless stated otherwise on an orbital shaker set to 50 rpm.

The acquisition and analysis software GenePix Pro 6.0 is used to generate from the scanner images gpr-files containing the mean fluorescence intensity (MFI) values for each processed slide. The gpr-files are analyzed using the statistical programming language R.
For determination of the degree of on-chip protein expression by antibodies targeting the terminal 6xHis- or V5-tag, respectively, the acquired gpr-files are imported to R and each protein spot’s MFI is compared to the MFI values of the negative control spots (made from control PCR lacking DNA-template). A protein is considered to be expressed if its final MFI (either 6xHis or V5 signal) exceeds the mean MFI value of the control spots plus five standard deviations.
For analysis of proteome immunoassays, the acquired gpr-files of all relevant microarray experiments are imported into R, and a threshold is defined as mean MFI of all negative controls plus five standard deviations. Before moving on to marker selection, visual quality control is done to all scanned slides for identification of possible artifacts. In addition, each slide’s MFI values are plotted according to their position on the slide. This allows the recognition of technical effects on individual slides, like gradients of the background or of the MFI values. All antigens showing MFI values above threshold are considered to be reactive with antibodies of the respective patient serum sample. In order to allow comparisons between different slides, an MFI signal is calculated by:

MFI signal = (MFI of antigen)/(MFI of threshold)

An MFI signal > 1 indicates a significant reactivity with a certain antigen.

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